Case Study | World Data Lab
Figure 1: Youth emplyment-to-population ratio (EPR), Youth Not in Employment, Education or Training (NEET) and Youth Unemployment Rate (YUR).
Figure 2: Composition of Youth Population: NEET vs. Non-NEET Trends by Gender. OLF = Out of Labour Force.
Figure 3: NEET trends by gender. Top panel is all the age groups, bottom panel is for the younger youth (age group 15-24).For the younger youth, gender gap is higher in Kenya indicating young women are facing barriers to enter training/job market.
Figure 4: YUR by age group. YUR higher in Rwanda. New entrants experiencing higher YUR in Kenya. YUR = Youth Unemployment Rate.
Figure 5: EPR by education. Not enough jobs for skilled workforce. Available jobs favour low skilled workers in Kenya from 2025. While skilled workers are still more employable in Rwanda, observed trend in Kenya is catching up.
Figure 6: A shift from agricultural subsistence activities to low productivity service activities observed for Kenya.
Figure 7: YUR by gender. Rwanda more hit by COVID-19 between 2020-2021 then steady recovery up to 2024.